A-MAP (A Multivariate Analysis Program) – a software program to perform multivariate statistical analysis on metabolite data. 

• Input uses regions of interests (ROIs) based on reference view of a spectrum or reference selected peaks.

• Row-wise (sample-wise) normalization and column-wise (ROI-wise) normalization are provided:

  • Row-wise (sample-wise) normalization 

    • Total normalization – normalizing the total area by dividing by the sum of all values in the same row/sample 

    • Median normalization – dividing each data by its median value 

    • Probabilistic Quotient Normalization (PQN) normalization – divides the data by the most common scale factor between the spectra 

    • Raw – no normalization

  • Column-wise (ROI-wise) normalization

    • Pareto scaling – divide each value by square root of the standard deviation

    • Unit scaling – divide each value by standard deviation

    • Standard Normal Variate (SNV) scaling – subtracts each data by the mean and dividing it by its own standard deviation 

    • Raw – no data scaling

• Both normalization methods offer mean centering option.

• Two multivariate analysis options:

  • Principal Component Analysis (PCA)

    • Input: Created ROIs

    • Output: a PCA scatter plot, a Hierarchical Cluster Analysis (HCA) dendrogram plot of PCA results, and a table of PCA scatter plot data

  • Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) 

    • Input: selected cluster number of chosen clusters

    • Output: an ROC Curve plot of unprocessed data and 2-Component OPLS data, a PLS Scores plot showing data in selected cluster and not in selected cluster, and a data table of both ROC Curve plot and PLS Scores plot with R2 and Q2 values